Deploying Public Charging Stations for Battery Electric Vehicles on the Expressway Network Based on Dynamic Charging Demand

There is an obvious gap between the rapid growth of battery electric vehicle (BEV) intercity travel demand and the worse deployment of charging facilities on the expressway network. With the consideration of dynamic charging demand, a bilevel model is proposed to deploy charging stations for the expressway network. The upper model aims at determining the location of charging stations and the number of chargers in each station to minimize the construction cost and total BEV travel cost. The dynamic charging demand is obtained by the lower model, which is constructed as a multiclass dynamic traffic assignment model, including charging, queuing, and flow transmission processes. A genetic algorithm incorporating the method of successive averages is adopted to solve the bilevel model. A real case in the Shandong province of China is employed to evaluate the effectiveness of the proposed model and algorithm. The sensitivity analyses show that a high level of charging service can encourage the usage of BEVs. In addition, when the BEV percentage is at a low level, planners should give priority to the quantity and location to expand charging service coverage and BEV's travel range; then, with the increasing of BEV percentage, the construction emphasis should change to charging station's capacity.